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moved functions/ in the scripts dir

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Tanushree Tunstall 2021-06-11 11:11:39 +01:00
parent 0c3645705d
commit f6259aa517
6 changed files with 4 additions and 4 deletions
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126
scripts/plotting/functions/plotting_data.R
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@ -1,126 +0,0 @@
#!/usr/bin/env Rscript
#########################################################
# TASK: formatting data that will be used for various plots
#########################################################
# load libraries and functions
library(data.table)
library(dplyr)
#========================================================
# plotting_data(): formatting data for plots
# input args:
## input csv file
## lig cut off dist, default = 10 Ang
# output: list of 4 dfs, that need to be decompressed
## my_df
## my_df_u
## my_df_u_lig
## dup_muts
#========================================================
plotting_data <- function(infile_params, mcsm_lig_cutoff = 10) {
my_df = data.frame()
my_df_u = data.frame()
my_df_u_lig = data.frame()
dup_muts = data.frame()
cat(paste0("\nInput file to prepare for plotting:", infile_params, "\n") )
#===========================
# Read file: struct params
#===========================
my_df = read.csv(infile_params, header = T)
cat("\nInput dimensions:", dim(my_df))
#==================================
# add foldx outcome category
# and foldx scaled values
# This will enable to always have these variables available
# when calling for plots
#==================================
#------------------------------
# adding foldx scaled values
# scale data b/w -1 and 1
#------------------------------
n = which(colnames(my_df) == "ddg"); n
my_min = min(my_df[,n]); my_min
my_max = max(my_df[,n]); my_max
my_df$foldx_scaled = ifelse(my_df[,n] < 0
, my_df[,n]/abs(my_min)
, my_df[,n]/my_max)
# sanity check
my_min = min(my_df$foldx_scaled); my_min
my_max = max(my_df$foldx_scaled); my_max
if (my_min == -1 && my_max == 1){
cat("\nPASS: foldx ddg successfully scaled b/w -1 and 1"
, "\nProceeding with assigning foldx outcome category")
}else{
cat("\nFAIL: could not scale foldx ddg values"
, "Aborting!\n")
}
#------------------------------
# adding foldx outcome category
# ddg<0 = "Stabilising" (-ve)
#------------------------------
c1 = table(my_df$ddg < 0)
my_df$foldx_outcome = ifelse(my_df$ddg < 0, "Stabilising", "Destabilising")
c2 = table(my_df$ddg < 0)
if ( all(c1 == c2) ){
cat("\nPASS: foldx outcome successfully created")
}else{
cat("\nFAIL: foldx outcome could not be created. Aborting!\n")
exit()
}
#==================================
# extract unique mutation entries
#==================================
# check for duplicate mutations
if ( length(unique(my_df$mutationinformation)) != length(my_df$mutationinformation)){
cat(paste0("\nCAUTION:", " Duplicate mutations identified"
, "\nExtracting these...\n"))
#cat(my_df[duplicated(my_df$mutationinformation),])
dup_muts = my_df[duplicated(my_df$mutationinformation),]
dup_muts_nu = length(unique(dup_muts$mutationinformation))
cat(paste0("\nDim of duplicate mutation df:", nrow(dup_muts)
, "\nNo. of unique duplicate mutations:", dup_muts_nu
, "\n\nExtracting df with unique mutations only\n"))
my_df_u = my_df[!duplicated(my_df$mutationinformation),]
}else{
cat(paste0("\nNo duplicate mutations detected\n"))
my_df_u = my_df
}
upos = unique(my_df_u$position)
cat("\nDim of clean df:"); cat(dim(my_df_u), "\n")
cat("\nNo. of unique mutational positions:"); cat(length(upos), "\n")
#===============================================
# extract mutations <10 Angstroms and symbol
#===============================================
table(my_df_u$ligand_distance<mcsm_lig_cutoff)
my_df_u_lig = my_df_u[my_df_u$ligand_distance <mcsm_lig_cutoff,]
cat(paste0("There are ", nrow(my_df_u_lig), " sites lying within 10\u212b of the ligand\n"))
# return list of DFs
#return(list(my_df, my_df_u, my_df_u_lig, dup_muts))
#df_names = c("my_df", "my_df_u", "my_df_u_lig", "dup_muts")
all_df = list(my_df, my_df_u, my_df_u_lig, dup_muts)
#all_df = Map(setNames, all_df, df_names)
return(all_df)
}
########################################################################
# end of data extraction and cleaning for plots #
########################################################################